---
library_name: transformers
license: mit
base_model: xlnet/xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cs221-xlnet-large-cased-eng-finetuned-remove-neutral-20-epochs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# cs221-xlnet-large-cased-eng-finetuned-remove-neutral-20-epochs

This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4332
- F1: 0.78
- Roc Auc: 0.8345
- Accuracy: 0.4901

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.5992        | 1.0   | 64   | 0.5778          | 0.4728 | 0.6331  | 0.1897   |
| 0.5534        | 2.0   | 128  | 0.4896          | 0.6557 | 0.7409  | 0.3004   |
| 0.4278        | 3.0   | 192  | 0.4141          | 0.7192 | 0.7893  | 0.3775   |
| 0.357         | 4.0   | 256  | 0.4215          | 0.7112 | 0.7818  | 0.4209   |
| 0.2832        | 5.0   | 320  | 0.3839          | 0.7644 | 0.8258  | 0.4289   |
| 0.2142        | 6.0   | 384  | 0.3746          | 0.7745 | 0.8293  | 0.4881   |
| 0.1625        | 7.0   | 448  | 0.4357          | 0.7704 | 0.8269  | 0.4763   |
| 0.1169        | 8.0   | 512  | 0.4332          | 0.78   | 0.8345  | 0.4901   |
| 0.0805        | 9.0   | 576  | 0.5132          | 0.7714 | 0.8320  | 0.4526   |
| 0.0624        | 10.0  | 640  | 0.4989          | 0.7735 | 0.8298  | 0.4625   |
| 0.0509        | 11.0  | 704  | 0.5205          | 0.7736 | 0.8315  | 0.4644   |
| 0.0294        | 12.0  | 768  | 0.5289          | 0.7767 | 0.8322  | 0.4763   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0